Optimizing RAG Document Pipelines With Docling
KhuyenTran16 · x · 2026-07-14
This article explores using the Docling library to build high-quality AI document processing pipelines. It points out that merely extracting plain text is insufficient; preserving structural relationships—such as table row-column mappings, chart titles, layout, and logical chunk boundaries—is crucial for retrievability. Docling converts files like PDFs into structured objects and exports them as Markdown or JSON. The piece provides a hands-on demonstration of integrating Docling into a RAG pipeline, covering the entire workflow from conversion and chunking to vector storage.
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